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  • × theme_ss:"Social tagging"
  1. Kruk, S.R.; Kruk, E.; Stankiewicz, K.: Evaluation of semantic and social technologies for digital libraries (2009) 0.03 
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    Abstract
    Libraries are the tools we use to learn and to answer our questions. The quality of our work depends, among others, on the quality of the tools we use. Recent research in digital libraries is focused, on one hand on improving the infrastructure of the digital library management systems (DLMS), and on the other on improving the metadata models used to annotate collections of objects maintained by DLMS. The latter includes, among others, the semantic web and social networking technologies. Recently, the semantic web and social networking technologies are being introduced to the digital libraries domain. The expected outcome is that the overall quality of information discovery in digital libraries can be improved by employing social and semantic technologies. In this chapter we present the results of an evaluation of social and semantic end-user information discovery services for the digital libraries.
    Date
    1. 8.2010 12:35:22
  2. Qin, C.; Liu, Y.; Mou, J.; Chen, J.: User adoption of a hybrid social tagging approach in an online knowledge community (2019) 0.02 
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    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 71(2019) no.2, S.155-175
  3. Yi, K.: ¬A semantic similarity approach to predicting Library of Congress subject headings for social tags (2010) 0.02 
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    Abstract
    Social tagging or collaborative tagging has become a new trend in the organization, management, and discovery of digital information. The rapid growth of shared information mostly controlled by social tags poses a new challenge for social tag-based information organization and retrieval. A plausible approach for this challenge is linking social tags to a controlled vocabulary. As an introductory step for this approach, this study investigates ways of predicting relevant subject headings for resources from social tags assigned to the resources. The prediction of subject headings was measured by five different similarity measures: tf-idf, cosine-based similarity (CoS), Jaccard similarity (or Jaccard coefficient; JS), Mutual information (MI), and information radius (IRad). Their results were compared to those by professionals. The results show that a CoS measure based on top five social tags was most effective. Inclusions of more social tags only aggravate the performance. The performance of JS is comparable to the performance of CoS while tf-idf is comparable with up to 70% less than the best performance. MI and IRad have inferior performance compared to the other methods. This study demonstrates the application of the similarity measuring techniques to the prediction of correct Library of Congress subject headings.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.8, S.1658-1672
  4. Rorissa, A.: ¬A comparative study of Flickr tags and index terms in a general image collection (2010) 0.02 
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    Abstract
    Web 2.0 and social/collaborative tagging have altered the traditional roles of indexer and user. Traditional indexing tools and systems assume the top-down approach to indexing in which a trained professional is responsible for assigning index terms to information sources with a potential user in mind. However, in today's Web, end users create, organize, index, and search for images and other information sources through social tagging and other collaborative activities. One of the impediments to user-centered indexing had been the cost of soliciting user-generated index terms or tags. Social tagging of images such as those on Flickr, an online photo management and sharing application, presents an opportunity that can be seized by designers of indexing tools and systems to bridge the semantic gap between indexer terms and user vocabularies. Empirical research on the differences and similarities between user-generated tags and index terms based on controlled vocabularies has the potential to inform future design of image indexing tools and systems. Toward this end, a random sample of Flickr images and the tags assigned to them were content analyzed and compared with another sample of index terms from a general image collection using established frameworks for image attributes and contents. The results show that there is a fundamental difference between the types of tags and types of index terms used. In light of this, implications for research into and design of user-centered image indexing tools and systems are discussed.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.11, S.2230-2242
  5. Hsu, M.-H.; Chen, H.-H.: Efficient and effective prediction of social tags to enhance Web search (2011) 0.02 
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    Abstract
    As the web has grown into an integral part of daily life, social annotation has become a popular manner for web users to manage resources. This method of management has many potential applications, but it is limited in applicability by the cold-start problem, especially for new resources on the web. In this article, we study automatic tag prediction for web pages comprehensively and utilize the predicted tags to improve search performance. First, we explore the stabilizing phenomenon of tag usage in a social bookmarking system. Then, we propose a two-stage tag prediction approach, which is efficient and is effective in making use of early annotations from users. In the first stage, content-based ranking, candidate tags are selected and ranked to generate an initial tag list. In the second stage, random-walk re-ranking, we adopt a random-walk model that utilizes tag co-occurrence information to re-rank the initial list. The experimental results show that our algorithm effectively proposes appropriate tags for target web pages. In addition, we present a framework to incorporate tag prediction in a general web search. The experimental results of the web search validate the hypothesis that the proposed framework significantly enhances the typical retrieval model.
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.8, S.1473-1487
  6. Wei, W.; Ram, S.: Utilizing sozial bookmarking tag space for Web content discovery : a social network analysis approach (2010) 0.02 
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    Abstract
    Social bookmarking has gained popularity since the advent of Web 2.0. Keywords known as tags are created to annotate web content, and the resulting tag space composed of the tags, the resources, and the users arises as a new platform for web content discovery. Useful and interesting web resources can be located through searching and browsing based on tags, as well as following the user-user connections formed in the social bookmarking community. However, the effectiveness of tag-based search is limited due to the lack of explicitly represented semantics in the tag space. In addition, social connections between users are underused for web content discovery because of the inadequate social functions. In this research, we propose a comprehensive framework to reorganize the flat tag space into a hierarchical faceted model. We also studied the structure and properties of various networks emerging from the tag space for the purpose of more efficient web content discovery. The major research approach used in this research is social network analysis (SNA), together with methodologies employed in design science research. The contribution of our research includes: (i) a faceted model to categorize social bookmarking tags; (ii) a relationship ontology to represent the semantics of relationships between tags; (iii) heuristics to reorganize the flat tag space into a hierarchical faceted model using analysis of tag-tag co-occurrence networks; (iv) an implemented prototype system as proof-of-concept to validate the feasibility of the reorganization approach; (v) a set of evaluations of the social functions of the current networking features of social bookmarking and a series of recommendations as to how to improve the social functions to facilitate web content discovery.
    Content
    A Dissertation Submitted to the Faculty of the COMMITTEE ON BUSINESS ADMINISTRATION In Partial Fulfillment of the Requirements For the Degree of DOCTOR OF PHILOSOPHY WITH A MAJOR IN MANAGEMENT In the Graduate College THE UNIVERSITY OF ARIZONA. Vgl.: http://hdl.handle.net/10150/195123. Vgl. auch: https://www.semanticscholar.org/paper/Utilizing-social-bookmarking-tag-space-for-web-a-Ram-Wei/da9e7e5ee771008b741af7176d3f0d67128d1dca.
  7. Niemann, C.: Tag-Science : Ein Analysemodell zur Nutzbarkeit von Tagging-Daten (2011) 0.02 
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    Source
    ¬Die Kraft der digitalen Unordnung: 32. Arbeits- und Fortbildungstagung der ASpB e. V., Sektion 5 im Deutschen Bibliotheksverband, 22.-25. September 2009 in der Universität Karlsruhe. Hrsg: Jadwiga Warmbrunn u.a
  8. Hammond, T.; Hannay, T.; Lund, B.; Flack, M.: Social bookmarking tools (II) : a case study - Connotea (2005) 0.01 
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    Abstract
    Connotea is a free online reference management and social bookmarking service for scientists created by Nature Publishing Group. While somewhat experimental in nature, Connotea already has a large and growing number of users, and is a real, fully functioning service. The label 'experimental' is not meant to imply that the service is any way ephemeral or esoteric, rather that the concept of social bookmarking itself and the application of that concept to reference management are both recent developments. Connotea is under active development, and we are still in the process of discovering how people will use it. In addition to Connotea being a free and public service, the core code is freely available under an open source license. Connotea was conceived from the outset as an online, social tool. Seeing the possibilities that del.icio.us was opening up for its users in the area of general web linking, we realised that scholarly reference management was a similar problem space. Connotea was designed and developed late in 2004, and soft-launched at the end of December 2004. Usage has grown over the past several months, to the point where there is now enough data in the system for interesting second-order effects to emerge. This paper will start by giving an overview of Connotea, and will outline the key concepts and describe its main features. We will then take the reader on a brief guided tour, show some of the aforementioned second-order effects, and end with a discussion of Connotea's likely future direction.
  9. Kuchler, T.; Pawlowski, J.M.; Zimmermann, V.: Social Tagging and Open Content : a concept for the future of e-learning and knowledge management? (2008) 0.01 
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    Abstract
    Open Content is a promising concept for e-learning and knowledge management. It can improve sharing and re-using educational resources and create new business opportunities. However, in contrast to open source software, these opportunities have not yet been adopted by a wide community. This article discusses barriers and opportunities. The Content Explosion Model shows how content can be re-used and adapted to increase sharing and distributing Open Content. Social tagging is discussed, on the basis of an implementation example (SLIDESTAR), as a means of fostering content exchange on a content community platform.
  10. Yi, K.: Harnessing collective intelligence in social tagging using Delicious (2012) 0.01 
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    Date
    25.12.2012 15:22:37
    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.12, S.2488-2502
  11. Choi, Y.; Syn, S.Y.: Characteristics of tagging behavior in digitized humanities online collections (2016) 0.01 
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    Date
    21. 4.2016 11:23:22
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.5, S.1089-1104
  12. Bentley, C.M.; Labelle, P.R.: ¬A comparison of social tagging designs and user participation (2008) 0.01 
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    Abstract
    Social tagging empowers users to categorize content in a personally meaningful way while harnessing their potential to contribute to a collaborative construction of knowledge (Vander Wal, 2007). In addition, social tagging systems offer innovative filtering mechanisms that facilitate resource discovery and browsing (Mathes, 2004). As a result, social tags may support online communication, informal or intended learning as well as the development of online communities. The purpose of this mixed methods study is to examine how undergraduate students participate in social tagging activities in order to learn about their motivations, behaviours and practices. A better understanding of their knowledge, habits and interactions with such systems will help practitioners and developers identify important factors when designing enhancements. In the first phase of the study, students enrolled at a Canadian university completed 103 questionnaires. Quantitative results focusing on general familiarity with social tagging, frequently used Web 2.0 sites, and the purpose for engaging in social tagging activities were compiled. Eight questionnaire respondents participated in follow-up semi-structured interviews that further explored tagging practices by situating questionnaire responses within concrete experiences using popular websites such as YouTube, Facebook, Del.icio.us, and Flickr. Preliminary results of this study echo findings found in the growing literature concerning social tagging from the fields of computer science (Sen et al., 2006) and information science (Golder & Huberman, 2006; Macgregor & McCulloch, 2006). Generally, two classes of social taggers emerge: those who focus on tagging for individual purposes, and those who view tagging as a way to share or communicate meaning to others. Heavy del.icio.us users, for example, were often focused on simply organizing their own content, and seemed to be conscientiously maintaining their own personally relevant categorizations while, in many cases, placing little importance on the tags of others. Conversely, users tagging items primarily to share content preferred to use specific terms to optimize retrieval and discovery by others. Our findings should inform practitioners of how interaction design can be tailored for different tagging systems applications, and how these findings are positioned within the current debate surrounding social tagging among the resource discovery community. We also hope to direct future research in the field to place a greater importance on exploring the benefits of tagging as a socially-driven endeavour rather than uniquely as a means of managing information.
    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  13. Tennis, J.T.: Measured time : imposing a temporal metric to classificatory structures 0.01 
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    Abstract
    Describes three units of time helpful for understanding and evaluating classificatory structures: long time (versions and states of classification schemes), short time (the act of indexing as repeated ritual or form), and micro-time (where stages of the interpretation process of indexing are separated out and inventoried). Concludes with a short discussion of how time and the impermanence of classification also conjures up an artistic conceptualization of indexing, and briefly uses that to question the seemingly dominant understanding of classification practice as outcome of scientific management and assembly line thought.
  14. Komus, A.; Wauch, F.: Wikimanagement : was Unternehmen von Social-Software und Web 2.0 lernen können (2008) 0.01 
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    Content
    Inhalt: I. Wie funktionieren Social Software-Angebote? II. Welchen Erklärungsbeitrag leisten bestehende Organisationsansätze und welche Schlüsse muss die Organisationslehre aus den Erfahrungen ziehen? III. Welches sind die Erfolgsfaktoren von Social Software und wie lassen sich Technologie und Erfolgsfaktoren in das Management übertragen und in Unternehmen nutzen?
    RSWK
    Management / Soziale Software / Leitbild
    Subject
    Management / Soziale Software / Leitbild
  15. Vander Wal, T.: Welcome to the Matrix! (2008) 0.01 
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    Abstract
    My keynote at the workshop "Social Tagging in Knowledge Organization" was a great opportunity to make and share new experiences. For the first time ever, I sat in my office at home and gave a live web video presentation to a conference audience elsewhere on the globe. At the same time, it was also an opportunity to premier my conceptual model "Matrix of Perception" to an interdisciplinary audience of researchers and practitioners with a variety of backgrounds - reaching from philosophy, psychology, pedagogy and computation to library science and economics. The interdisciplinary approach of the conference is also mirrored in the structure of this volume, with articles on the theoretical background, the empirical analysis and the potential applications of tagging, for instance in university libraries, e-learning, or e-commerce. As an introduction to the topic of "social tagging" I would like to draw your attention to some foundation concepts of the phenomenon I have racked my brain with for the last few month. One thing I have seen missing in recent research and system development is a focus on the variety of user perspectives in social tagging. Different people perceive tagging in complex variegated ways and use this form of knowledge organization for a variety of purposes. My analytical interest lies in understanding the personas and patterns in tagging systems and in being able to label their different perceptions. To come up with a concise picture of user expectations, needs and activities, I have broken down the perspectives on tagging into two different categories, namely "faces" and "depth". When put together, they form the "Matrix of Perception" - a nuanced view of stakeholders and their respective levels of participation.
    Date
    22. 6.2009 9:15:45
  16. Wang, J.; Clements, M.; Yang, J.; Vries, A.P. de; Reinders, M.J.T.: Personalization of tagging systems (2010) 0.01 
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    Source
    Information processing and management. 46(2010) no.1, S.58-70
  17. Konkova, E.; Göker, A.; Butterworth, R.; MacFarlane, A.: Social tagging: exploring the image, the tags, and the game (2014) 0.01 
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    Abstract
    Large image collections on the Web need to be organized for effective retrieval. Metadata has a key role in image retrieval but rely on professionally assigned tags which is not a viable option. Current content-based image retrieval systems have not demonstrated sufficient utility on large-scale image sources on the web, and are usually used as a supplement to existing text-based image retrieval systems. We present two social tagging alternatives in the form of photo-sharing networks and image labeling games. Here we analyze these applications to evaluate their usefulness from the semantic point of view, investigating the management of social tagging for indexing. The findings of the study have shown that social tagging can generate a sizeable number of tags that can be classified as in terpretive for an image, and that tagging behaviour has a manageable and adjustable nature depending on tagging guidelines.
  18. Huang, S.-L.; Lin, S.-C.; Chan, Y.-C.: Investigating effectiveness and user acceptance of semantic social tagging for knowledge sharing (2012) 0.01 
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    Source
    Information processing and management. 48(2012) no.4, S.599-617
  19. Santini, M.: Zero, single, or multi? : genre of web pages through the users' perspective (2008) 0.01 
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    Source
    Information processing and management. 44(2008) no.2, S.702-737
  20. Hänger, C.: Knowledge management in the digital age : the possibilities of user generated content (2009) 0.01 
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